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Quantitative Analytics Manager

  • Artificial Intelligence & Quantitative Analytics
  • Full time
  • R-241970

About this role:

The Enterprise Analytics and Data Science (EADS) organization at Wells Fargo is looking for a Data Science Manager to join the AI/ML team. Primary role is to support AI/ML model refresh, performance monitoring, data analysis, model implementation, model production, delivery of model results. Additionally, the role will also contribute towards research activities and development of automated monitoring framework for advanced AI/ML algorithms. It is a leadership role with people management involved.

In this role, you will:

  • Need to lead and also work individually on data science projects and work closely with business partners across the organization.
  • Recruit, develop and nurture team for best in class project delivery and capability development
  • Perform various complex activities related to statistical/machine learning models. Provide analytical support for productionalizing, evaluating, implementing, monitoring and executing models across business verticals using technologies including but not limited to Python, Spark, and H2O etc.
  • Develop dynamic dashboards; analyze key risk parameters to help understand changes in business and model performance
  • Identify opportunities and deliver process improvements, standardization, rationalization and automations. Enhance and standardize performance analysis, reporting packages
  • Maintain documentation for implementation and monitoring processes across the team with focus on standardization of controls
  • Provide thought leadership and drive innovation, better solutions, efficiency enhancement for existing and new products

Required Qualifications:

  • BS degree or higher in a quantitative field such as applied math, statistics, physics, accounting, finance, economics, econometrics, or business/social and behavioral sciences with a quantitative emphasis
  • Bachelors or Master’s degree in engineering field like computer science and engineering, Information technology, Electrical Engineering, Electronics and Telecommunication Engineering etc.
  • 12+ years of relevant experience
  • 5+ years of leadership experience
  • Experience in implementing, productionalizing, model monitoring of supervised, unsupervised and semi-supervised model techniques including but not limited to Random Forest, GBM, Ridge-Lasso-ElasticNet, XGboost etc. Time-series techniques like Arima (and the family), Arch, Garch etc.
  • Excellent understanding of model metrics including AUC, ROC, CAP-curve, F-statistics etc. with clear understanding of how model performance is tuned
  • Excellent hands-on on with Drift and Lift analysis and related model monitoring metrics
  • Experience in implementing, model monitoring of Deep-learning, Artificial intelligence techniques like ANN, CNN, DNN, RNN etc. and how to strategize deep-learning layer and activations.
  • Expertise in one or more analytic tools like : Python (with Anaconda), PySpark,  H2O
  • Experience in one or more of Big Data skills – SQL, Aster, Teradata, Hadoop, SPARK,
  • Model Monitoring for NLP, Text mining, Image/Voice processing, digital analytics, deep learning, machine learning models
  • Demonstrate excellent organization skills throughout the development of analytical solutions (data analysis documentation, hypothesis documentation, code management, etc.).
  • Strong ability to develop partnerships and collaborate with other business and functional areas

Desired Qualifications:

  • Output deployment using appropriate technologies (HTML5, Shiny, Flask)
  • Working expertise in Tensorflow, Keras or Pytorch would be added advantage
  • Strong knowledge of distributed computing and Spark programming
  • Knowledge of one or more of public cloud environments (GCP, Azure, AWS) – especially on AI/ML related suites
  • Knowledge of banking industry and products in at least one of the LOB such as credit cards, mortgage, deposits, loans or wealth management etc.
  • Knowledge of functional area such as risk, marketing, operations or supply chain in banking industry.
  • Proved track record in research and innovation and visible presence in industry

Job Expectations:

  • As described above

We Value Diversity

At Wells Fargo, we believe in diversity, equity and inclusion in the workplace; accordingly, we welcome applications for employment from all qualified candidates, regardless of race, color, gender, national origin, religion, age, sexual orientation, gender identity, gender expression, genetic information, individuals with disabilities, pregnancy, marital status, status as a protected veteran or any other status protected by applicable law.

Employees support our focus on building strong customer relationships balanced with a strong risk mitigating and compliance-driven culture which firmly establishes those disciplines as critical to the success of our customers and company. They are accountable for execution of all applicable risk programs (Credit, Market, Financial Crimes, Operational, Regulatory Compliance), which includes effectively following and adhering to applicable Wells Fargo policies and procedures, appropriately fulfilling risk and compliance obligations, timely and effective escalation and remediation of issues, and making sound risk decisions. There is emphasis on proactive monitoring, governance, risk identification and escalation, as well as making sound risk decisions commensurate with the business unit’s risk appetite and all risk and compliance program requirements.

Candidates applying to job openings posted in US: All qualified applicants will receive consideration for employment without regard to race, color, religion, age, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.

Candidates applying to job openings posted in Canada: Applications for employment are encouraged from all qualified candidates, including women, persons with disabilities, aboriginal peoples and visible minorities. Accommodation for applicants with disabilities is available upon request in connection with the recruitment process.

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